research-article

Stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay

Authors:

Yajuan LiuAuthors Info & Claims

Neurocomputing, Volume 173, Issue P3

Pages 1706 - 1714

https://doi.org/10.1016/j.neucom.2015.09.043

Published: 15 January 2016 Publication History

Abstract

In this paper, the problem of stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay is investigated. By constructing a new Lyapunov-Krasovskii functional and employing a novel summation inequality which is a discrete-time counterpart of the Wirtinger-based integral inequality, a less conservative robust stability criterion is derived in terms of linear matrix inequalities. Furthermore, a new sufficient condition is established to assure the considered neural networks to be passive. Several numerical examples are provided to demonstrate the effectiveness of the proposed method.

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Cited By

Sowmiya CRaja RCao JRajchakit GAlsaedi A(2020)A delay‐dependent asymptotic stability criteria for uncertain BAM neural networks with leakage and discrete time‐varying delaysAsian Journal of Control10.1002/asjc.218422:5(1880-1891)Online publication date: 14-Sep-2020
https://dl.acm.org/doi/10.1002/asjc.2184
Badie KAlfidi MChalh Z(2020)Reliable control for 2‐D discrete switched systems with state delays and actuator failuresInternational Journal of Adaptive Control and Signal Processing10.1002/acs.315634:10(1383-1404)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1002/acs.3156
Zaidi IChtourou MDjemel M(2019)Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training AlgorithmInternational Journal of Automation and Computing10.1007/s11633-017-1062-216:2(213-225)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11633-017-1062-2
Show More Cited By

Stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay
1. Mathematics of computing
  1. Mathematical analysis

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cover image Neurocomputing

Neurocomputing Volume 173, Issue P3

January 2016

1666 pages

ISSN:0925-2312

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Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 15 January 2016

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Cited By

Sowmiya CRaja RCao JRajchakit GAlsaedi A(2020)A delay‐dependent asymptotic stability criteria for uncertain BAM neural networks with leakage and discrete time‐varying delaysAsian Journal of Control10.1002/asjc.218422:5(1880-1891)Online publication date: 14-Sep-2020
https://dl.acm.org/doi/10.1002/asjc.2184
Badie KAlfidi MChalh Z(2020)Reliable control for 2‐D discrete switched systems with state delays and actuator failuresInternational Journal of Adaptive Control and Signal Processing10.1002/acs.315634:10(1383-1404)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1002/acs.3156
Zaidi IChtourou MDjemel M(2019)Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training AlgorithmInternational Journal of Automation and Computing10.1007/s11633-017-1062-216:2(213-225)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11633-017-1062-2
Liu LZhu SWu BWang Y(2018)On designing state estimators for discrete-time recurrent neural networks with interval-like time-varying delaysNeurocomputing10.1016/j.neucom.2018.01.054286:C(67-74)Online publication date: 19-Apr-2018
https://dl.acm.org/doi/10.1016/j.neucom.2018.01.054
Kong FFang X(2018)Pseudo almost periodic solutions of discrete-time neutral-type neural networks with delaysApplied Intelligence10.1007/s10489-018-1146-x48:10(3332-3345)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1007/s10489-018-1146-x
Saravanakumar RRajchakit GAli MXiang ZJoo Y(2018)Robust extended dissipativity criteria for discrete-time uncertain neural networks with time-varying delaysNeural Computing and Applications10.1007/s00521-017-2974-z30:12(3893-3904)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s00521-017-2974-z
Ma YZheng Y(2018)Delay-dependent stochastic stability for discrete singular neural networks with Markovian jump and mixed time-delaysNeural Computing and Applications10.1007/s00521-016-2414-529:1(111-122)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s00521-016-2414-5
Sowmiya CRaja RCao JRajchakit G(2018)Enhanced result on stability analysis of randomly occurring uncertain parameters, leakage, and impulsive BAM neural networks with time‐varying delaysInternational Journal of Adaptive Control and Signal Processing10.1002/acs.288332:7(1010-1039)Online publication date: 3-Jul-2018
https://dl.acm.org/doi/10.1002/acs.2883
Ramasamy SNagamani GRadhika T(2017)Further Results on Dissipativity Criterion for Markovian Jump Discrete-Time Neural Networks with Two Delay Components Via Discrete Wirtinger Inequality ApproachNeural Processing Letters10.1007/s11063-016-9559-145:3(939-965)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1007/s11063-016-9559-1
Guo DNie ZYan L(2016)Theoretical analysis, numerical verification and geometrical representation of new three-step DTZD algorithm for time-varying nonlinear equations solvingNeurocomputing10.1016/j.neucom.2016.06.032214:C(516-526)Online publication date: 19-Nov-2016
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